Recommending of an item to a user

Abstract

The present disclose provides a method of recommending at least one item to a user, the method comprising: receiving the user's feedback on an item; predicting a user vector and an item vector related to the user in an online mode based on the received feedback; and recommending to the user an acceptable item based on the user vector and item vector.

What is claimed: 
     
         1 . A method of recommending at least one item to a user, the method comprising:
 receiving the user's feedback on an item;   predicting a user vector and an item vector related to the user in an online mode based on the received feedback; and   recommending to the user an acceptable item based on the predicted user vector and item vector.   
     
     
         2 . The method according to  claim 1 , further comprising:
 determining whether the user has any social information;   merging the social information with a user-item matrix to predict the user vector and the item vector.   
     
     
         3 . The method according to  claim 2 , wherein the social information is expressed as a social network matrix. 
     
     
         4 . The method according to  claim 2 , further comprising:
 determining whether the user has any location information;   merging the location information with the user-item matrix to predict the user and item vectors.   
     
     
         5 . The method according to  claim 4 , wherein the location information is expressed as a location network matrix. 
     
     
         6 . The method according to  claim 1 , wherein the step of recommending the user the acceptable item is further based on the user's preference. 
     
     
         7 . A recommender system, comprising:
 at least one processor and a recommendation engine to:
 generate a user matrix based on received user's information; 
 generate an item matrix based on information of one or more items; 
 predict a rating value of at least one item in an online mode based on a user vector in the user matrix and an item vector in the item matrix; and 
 recommend to a user an acceptable item based on the ranking of the predicted rating value. 
   
     
     
         8 . The recommender system according to  claim 7 , where the recommender system further includes at least one element of a group comprised of:
 a user data module to store at least one of the user's information and the user's feedback;   an item module to store information of all items to be recommended; and   a repository to store at least one of the user matrix, item matrix and a user-item matrix.   
     
     
         9 . The online recommender system according to  claim 7 , wherein the user's information further includes at least one of social information and location information for use by the recommendation engine to recommend the acceptable item. 
     
     
         10 . Apparatus comprising:
 a processor; and   a memory storing computer readable instructions executable by the processor to:
 update an initial user-item matrix by using an online prediction algorithm; and 
 recommend to a user an acceptable item based on ratings of items in the updated user-item matrix. 
   
     
     
         11 . The apparatus according to  claim 10 , wherein the memory further stores instructions which, when executed by the processor, cause the processor to:
 generate the initial user-item rating matrix based on a user's information.   
     
     
         12 . The apparatus according to  claim 10 , wherein the memory further stores instructions which, when executed by the processor, cause the processor to:
 generate the initial user-item rating matrix based on user's historical data.   
     
     
         13 . The apparatus according to  claim 10 , wherein the online predication algorithm includes a local objective function for an online mode. 
     
     
         14 . The apparatus according to  claim 13 , wherein the local objective function is to be minimized. 
     
     
         15 . The apparatus according to  claim 13 , wherein the local objective function is a root mean square function.